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Before you enroll

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Your receipt

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Feature Engineering for ML

Learn how to preprocess data and engineer new features to improve your machine-learning models.
Who Is This For?

Data Scientists interested in improving the performance of their machine learning models.

Any prerequisites?

Python

  • Intermediate Python knowledge, including data structures, loops, and functions.
  • Experience with data manipulation using the Pandas library.

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Statistics and ML

  • Knowledge of linear and logistic regression and basic principles of machine learning.
  • Note: the following Modal courses would successfully prepare a learner for this course: Python for Data Science, Preparing Data for Analysis with Python, Applying Statistical Thinking with Python, and Introduction to Supervised Machine Learning.
What will I be able to do after this Course?
  • Prepare data for input into a machine learning model, including feature creation, transformation, scaling, and categorical encoding.
  • Use feature importance, wrapper methods, and embedded methods to filter and select features for inclusion in a machine-learning model.
  • Reduce the dimensionality of a dataset using principal component analysis and partial least squares.
Reimbursement FAQ

Course Overview

Sprint 1: Data Transformations and Encoding
Create new features, transform existing features using methods such as standardization and normalization, and encode categorical variables using a variety of methods.
Sprint 2: Feature Selection
Select features for inclusion in a machine learning model using filter methods, step-forward and backward algorithms, and regularization.
Sprint 3: Dimensionality Reduction
Use methods such as principal component analysis (PCA) and partial least squares to reduce the dimensionality of a dataset without losing a large amount of information.

What’s in a Modal course?

1:1 Coaching
Receive personal guidance, instruction, and motivation from real, practicing industry experts.
Real-world simulations
Practical coursework blends simulated and real-world projects, ensuring you are building job-ready skills.
Integrated code editor
In-browser coding environment mitigates challenges while enabling paired programming and inline feedback.
Structure & flexibility
Engage with content when your schedule allows. Our assignments and deadlines help you stay on track and our coaches keep you accountable.
Individual guidance
Courses for a variety of career goals, skill needs, and company objectives, ensuring learning is both relevant and productive.
Capstones projects
Challenging and satisfying capstone projects allow you to demonstrate the skills you’ve learned, while reinforcing collaboration and business skills.

Meet our coaches

Linda Liu
Director, Data Science & Analytics

Working with the learners makes it an incredibly rewarding journey. The shared excitement and collaborative growth highlight the entire fulfilling coaching experience!

Nataliia Maksimova
Director, Business Intelligence

It's incredibly inspiring to introduce people to the fascinating world of data. Sharing my passion for data and showing that it's not just dry numbers but a creative field where you can grow and innovate is deeply rewarding.

Udit Mehrotra
Senior Data Scientist

Seeing the growth in my learners is not only heartening but also assuring because I know I had a significant role to play in shaping their journey.

Interested in buying multiple seats for your team?
Contact us